Characterization of the Spiritwood Valley Aquifer, North Dakota, Using a Helicopter Time-domain EM System
Bibliographic record
Abstract
Summary Buried valley aquifers, consisting of permeable sand and gravel deposits in eroded bedrock valleys, are important sources of groundwater supply in many regions of the United States and Canada. But they have been difficult to define because they are often partially eroded, have complex lithology and are hidden within thick glacial overburden. Recent investigations of the Spiritwood Valley aquifer in Manitoba by the GSC using helicopter time-domain EM have provided the impetus for the North Dakota State Water Commission to fly a VTEM helicopter TDEM survey in the Jamestown, ND region in October, 2016. The VTEM data collected over the Spiritwood-JT block allowed for geological mapping from near surface to depth, in spite of relatively weak resistivity contrasts (<10X). The VTEM data were inverted with the 1D GALEISBSTDEM algorithm to produce resistivity-depth models. These models were able to resolve the location and depths to the top and bottom of the Spiritwood aquifer throughout the central portion of the block providing more detailed pictures of the aquifer’s geometry. In addition to resolving the main Spiritwood aquifer as well as its deeper channels, the VTEM data and models highlighted several smaller aquifers which cross-cut/branch-off from the main Spiritwood channel.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".